Top 5 social media phishing scams to avoid. » Mortgage Masters Group

Top 5 social media phishing scams to avoid. » Mortgage Masters Group

 · The attacker group behind this malware is also responsible for attacks against the White House, the Joint Chiefs of Staff, the State Department and other nation-state governments, such as Norway. This novel approach to weaponizing social media shows the need to analyze social media as a full lifecycle attack vector.

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How can you avoid smishing scams? hong says you should make sure to use different passwords for everything from your bank’s website and social media apps to your email account.

5. Avoid unknown. it’s always best to err on the side of caution by deleting the message, then potentially blocking the sender’s account and warning others to do the same. 6. Hang up and call back..

Spear-phishing is especially commonplace on social media sites like LinkedIn, where attackers can use multiple sources of information to craft a targeted attack email. To protect against this type of scam, organizations should conduct ongoing employee security awareness training that, among other things, discourages users from publishing.

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How to Avoid Phishing Scams. A phishing scam is a malicious attack attempting to trick the target into entering sensitive information. The hacker behind the phishing attack is often trying to acquire user names and passwords for financial systems, credit card information, PayPal login information, or other personal information to be exploited at a later time.

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"In the past five years, according to the FBI, this kind of fraud has cost US business $12.5 billion. That’s not a small figure by any kind of reckoning. If we’re talking about subtlety or lightness of touch, whaling is right at the top end of the spear-phishing spectrum.

5. Social Media in the Mix. With the explosion of Facebook, Twitter and other social media, more companies want to analyze the data these sites generate. New analytics applications have emerged to support statistical techniques such as natural language processing, sentiment analysis, and network analysis that aren’t part of the typical BI toolkit.

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